flowchart LR exposure(chemical) --> mediator(metabolite) mediator --> outcome(neurodevelopment) exposure --> outcome
ISGlobal
4/19/23
flowchart LR exposure(chemical) --> mediator(metabolite) mediator --> outcome(neurodevelopment) exposure --> outcome
A ExWAS kind of analysis with the dependent variable \(y\) being the outcome, and the independent variable \(x_i\) being the levels of EDC \(i\).
A XWAS analysis with the dependent variable \(m_i\) being the metabolite or protein \(i\), and the independent variable \(x_j\) being the levels of EDC \(j\).
A XWAS analysis with the dependent variable \(y\) being the outcome, and the independent variable \(m_i\) being the metabolite or protein \(i\).
flowchart LR
paper[Paper 3] --> rq1("RQ1
neuro~chemical")
paper --> rq2("RQ2
met~chemical")
paper --> rq3("RQ3
neuro~met")
rq1 --> rqReg("Observational study.
Method: Regression with MTPs.
Causal estimand: phi.
Uncertainty quantification: bootstrapping.")
rq1 --> rq1outNeg("Outcome negative control.
Method: Regression with GLMs/GAMs.
Uncertainty quantification: bootstrapping.")
rq1 --> rqLit("Literature search")
rq2 --> rqReg
rq2 --> rqCrossCohort("Cross-cohort comparison.
Method: Regression with GLMs/GAMs.
Uncertainty quantification: bootstrapping.")
rq2 --> rqLit
rq3 --> rqReg
rq3 --> rqCrossCohort
rq3 --> rq3mr("Mendelian Randomization.
Causal estimand: .")
glm), and data-adaptive semi-parametric models. Specifically, we will make use of the lmtp R package, in combination with TMLE and SL. We hypothesize the presence of residual confounding, especially due to genetic and parental factors, which would result in exaggeration of any true causal effect.outcome ~ chemical association, we will perform a literature search to compare the obtained results.omic ~ chemical with the expected modified associations (e.g., weaker or stronger).